CN115951270B - Permanent magnet synchronous motor external cable connection fault diagnosis method - Google Patents
Permanent magnet synchronous motor external cable connection fault diagnosis method Download PDFInfo
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Abstract
The invention discloses a method for diagnosing connection faults of an external cable of a permanent magnet synchronous motor, which comprises the following steps: inputting a zero-speed instruction to a rotating speed control module; injecting a rotating high-frequency voltage signal into the current control module; collecting and recording response current output by a controlled motor; filtering high-frequency components in the response current, and extracting features; and carrying out model training by using a support vector machine, judging whether an external cable connection fault occurs, and identifying the fault type. The invention realizes the cable connection fault diagnosis based on high-frequency signal injection and current response analysis at zero speed. The diagnosis strategy provided by the invention does not depend on salient pole effect of the motor, and can be applied to various permanent magnet synchronous motor control systems; the defect of a special diagnosis scheme aiming at the cable faults outside the motor control system in the existing research is overcome, and the problem that the existing general diagnosis scheme cannot realize effective diagnosis under the complex operation condition when the cable faults occur is solved.
Description
Technical Field
The invention relates to the technical field of high-frequency injection and the field of motor fault diagnosis, in particular to a method for diagnosing connection faults of three-phase power cables and position sensor output cables in a permanent magnet synchronous motor control system.
Background
Fault diagnosis and localization has become an important part of the field of permanent magnet synchronous motors. Motor fault detection techniques now fall generally into three categories: model-based methods, signal-based methods, and intelligent algorithm-based methods. Model-based diagnostic methods require accurate motor models. In engineering practice, actual motor parameters often deviate from the mathematical model. In the real-time operation process, the accuracy of parameters cannot be guaranteed. Therefore, a signal-based fault diagnosis method is proposed to improve the accuracy of diagnosis. Signal-based fault detection requires that a fault signal be obtained first, and then time and frequency domain features of the fault signal be extracted to determine the fault type and fault location.
In recent years, with the development of High-frequency injection technology, many fault diagnosis cases based on signal injection have also appeared, such as proposed by c.sun in High-Frequency Voltage Injection-Based Fault Detection of a Rotating Rectifier for a Wound-Rotor Synchronous Starter/Generator in the Stationary State, in which a High-frequency rotating voltage signal is injected into the stator winding of a permanent magnet synchronous motor, and then a High-frequency response current signal is extracted from the main pole stator excitation winding for fault detection.
Model-based and signal-based fault diagnosis rely on a combination of mathematical calculations and experimentation. Although the response signal-based system can perform accurate fault diagnosis, it is generally affected by specific motor parameters, and has low versatility for different types of control systems and different types of motors. With the help of an intelligent algorithm, the operation data of the motor can be collected, processed and analyzed under the condition that an accurate mathematical model is not established, and a corresponding input-output relationship is established, so that fault identification is realized. The support vector machine SVM is an intelligent classification algorithm in machine learning. The method solves the problem of local minimum values encountered in the training of the neural network, and is an intelligent learning algorithm based on the principle of minimizing structural errors. It can construct an optimal segmentation plane in a high-dimensional feature space through small sample learning and has high-precision input and output mapping capability. The basic idea is to establish a classification hyperplane as a decision plane to maximize the separation margin between positive and negative samples, and select optimal parameters such as a kernel function and a penalty coefficient to form a final fault classification model. In recent years, support vector machines have been widely used in the field of motor fault diagnosis.
Cable connection failure in motor control systems often results from improper operation, which can cause serious consequences such as rotor lock shaft, excessive current, motor burnout, etc. However, in the field of fault diagnosis, there is little research on cable connection faults in permanent magnet synchronous motor control systems. The stator inter-turn faults are of interest to a robust, on-line turn-fault detection technique for induction machines based on monitoring the sequence component impedance matrix and An Impedance Identification Approach to Sensitive Detection and Location of Stator Turn-to-Turn Faults in a Closed-Loop Multiple-Motor Drive, by t.g. habeltler et al, where the former article suggests that mathematical models of Motor external cable faults and stator inter-turn faults are similar, and that a general diagnostic strategy could theoretically be used. However, the latter article indicates that the practical diagnostic effect is limited because the operating environment under cable fault conditions is more complex and the fault phenomena are different.
Disclosure of Invention
Technical problems: the invention aims to provide a method for diagnosing connection faults of an external cable of a permanent magnet synchronous motor. In the zero-speed state, based on the rotary high-frequency voltage injection technology, a comprehensive diagnosis method is established for single faults and multiple faults caused by various cable misconnections such as two-phase exchange, single-phase disconnection, two-output cable exchange of a position sensor and the like in a three-phase power cable.
The technical scheme is as follows: the invention relates to a method for diagnosing connection faults of external cables of a permanent magnet synchronous motor, which is used for diagnosing connection faults of three-phase power cables and output cables of position sensors in a permanent magnet synchronous motor control system, wherein the control system consists of a rotating speed control module and a current control module, and the diagnosis method comprises the following steps of:
s1, inputting a zero-speed instruction to a rotating speed control module;
according to a permanent magnet synchronous motor voltage model and a back electromotive force model under a natural coordinate system:
in order to eliminate the influence of back electromotive force on the response of high-frequency injection, detecting faults before the motor starts to operate and timely removing the faults, and performing fault diagnosis at zero rotation speed and zero initial position;
s2, injecting a rotating high-frequency voltage signal into the current control module;
according to different types of injection signals, high-frequency signal injection is divided into voltage injection and current injection, and the control stability of the voltage signal is higher than that of the current signal; the voltage signal can be injected into the stator winding or the current control module, namely, the signal is directly injected into a direct axis, namely a d axis, and an intersecting axis, namely a q axis, of the current control module in a synchronous rotation coordinate system, so that the influence of coordinate transformation is avoided; the form of the injection voltage signal is mainly divided into rotation, pulse and square wave, wherein the steady state performance of the injection of the rotation voltage is best, and dq axis coupling existing in the current control process can be completely eliminated through coordinate transformation under the injection of the rotation voltage;
in the control system, two high-frequency voltage signals with a phase difference of 90 DEG are respectively injected into the d axis and the q axis of a current control module, wherein
Is the amplitude of the injection voltage, ">
Is the frequency of the injection voltage; />
Is a vector representation of the injection voltage in a synchronous rotating coordinate system;
s3, collecting and recording response current output by the controlled motor;
according to theoretical calculation, the response current output by the motor is related to the real-time position of the rotor, the amplitude of the high-frequency injection voltage and the sequence of the three-phase winding voltages of the stator, so that the cable faults of the motor control system can be reflected on the output response current;
s4, filtering high-frequency components in the response current, and extracting features;
filtering the output response current, and extracting a high-frequency component with the same amplitude as the injection voltage signal to be used as an original data set; extracting time domain features and frequency domain features of the original data set as feature value data of response current by using a feature extraction algorithm so as to enhance the accuracy of discrimination;
s5, carrying out model training by using a Support Vector Machine (SVM), judging whether an external cable connection fault occurs in the control system, and identifying the fault type;
in order to better describe the relationship between the fault data and the fault category of the controlled motor, accurate classification and identification are realized, and a motor operation data set is learned based on the basic principle of a support vector machine;
the motor responds to the characteristic value data of the current, a part of the characteristic value data is used as a training set to train an SVM model, and then relevant parameters are adjusted to achieve the highest classification precision aiming at each group of data sets; and the other part of data is used as a test set, the trained SVM model is used for offline classification, and the obtained fault diagnosis result is used as a reference, so that an operator can accurately remove the fault.
Wherein,,
the permanent magnet synchronous motor control system is that
Namely, a magnetic field directional control mode in which the direct current is set to zero, by setting the direct current in the current control module +.>
The zero setting mode is used for avoiding the demagnetization of the direct shaft, eliminating the direct shaft armature reaction of the permanent magnet synchronous motor, keeping the good magnetism of the permanent magnet used for excitation and improving the utilization rate of the conversion of the electric energy of the motor into mechanical energy.
The response current in the step S3 is continuously returned to the current control module in the step S2 in a negative feedback mode.
The failure of the connection of the output cables of the position sensor refers to the sequential exchange of the two output cables A, B of the incremental encoder and the rotary transformer, so that the real-time position and the actual position of the output motor rotor are in opposite numbers.
The three-phase power cable refers to a power line connected with the inverter and the motor three-phase stator winding, a control voltage signal is transmitted from the driver to the controlled motor through the power line, and response current is generated on the winding through electromagnetic induction.
The support vector machine used in step S5 is a C-type SVM, and the corresponding parameter S (svm_type) is set to
Incomplete classification is supported; the kernel function of the support vector machine selects a radial RBF kernel function, also called Gaussian kernel function, whose corresponding parameter t (kernel_type) is set to +.>
。
The original data set in the step S4 also comprises high-frequency negative sequence response current which carries the position information of the motor rotor and is not influenced by the rotor rotating speed and the sensor faults, and the high-frequency negative sequence response current can be used as one of the basis of fault diagnosis; and filtering out negative sequence components of the high-frequency response current by adopting a synchronous shafting filter SRFF, and jointly outputting the negative sequence components from a control system as an original data set.
The response current described in step S3, the sensor voltage output by the motor is converted via the voltage-current module.
The external cable connection fault diagnosis method is independent of the salient pole effect of the motor, and the permanent magnet synchronous motors with different magnetic pole structures and different functions can be used for diagnosing the cable connection fault of the motor.
The external cable connection fault diagnosis method is used for judging faults and determining fault phases with 100% accuracy under the conditions that two phase misconnection, single phase misconnection and single phase misconnection of the three-phase power cable occur simultaneously; when the cable misconnection fault occurs, judging whether the misconnection fault is positioned in the three-phase power cable or the position sensor with the accuracy of more than 98%; when the position sensor outputs the cable and the three-phase power cable simultaneously fail, the failure phase of the three-phase power cable is positioned with 100% accuracy.
The beneficial effects are that: the method for diagnosing the connection faults of the external cable of the permanent magnet synchronous motor has the following advantages:
1. the fault discrimination and fault phase determination with 100% accuracy are made for the two-phase misconnection, single-phase misconnection and the two-phase misconnection and single-phase misconnection of the three-phase power cable. The position of the misconnection fault can be determined with an accuracy exceeding 98% when the cable misconnection fault occurs. When the position sensor outputs the cable and the three-phase power cable simultaneously fail, the failure phase of the three-phase power cable is positioned with 100% accuracy.
2. The deduced response current equation and vector diagram under various fault states can be used as the reference for the subsequent researches about cable faults, inverter short circuits and open circuit faults.
3. The proposed diagnosis strategy is independent of salient pole effect of the motor, and can be applied to control systems of various built-in permanent magnet synchronous motors and surface-mounted permanent magnet synchronous motors to diagnose cable connection faults.
4. The defect of a special diagnosis scheme aiming at the cable faults outside the motor control system in the existing research is overcome, and the problem that the existing general diagnosis scheme cannot realize effective diagnosis under the complex operation condition when the cable faults occur is solved.
Drawings
Fig. 1 is a whole structure diagram of a permanent magnet synchronous motor control system constructed by the invention, wherein the structure performs rotating speed closed-loop control and is a motor speed control module.
Fig. 2 is a block diagram of a current control module in the motor control system structure shown in fig. 1.
FIG. 3 is a flow chart of a fault diagnosis algorithm used in the present invention.
Fig. 4 is a vector diagram of winding voltage and response current in a normal operation without failure according to the present invention.
Fig. 5a is a vector diagram of winding voltage and response current in a B, C phase power line misconnection fault condition.
Fig. 5b is a vector diagram of winding voltage and response current in a A, C phase power line misconnection fault condition.
Fig. 5c is a vector diagram of winding voltage and response current in a A, B phase power line misconnection fault condition.
Fig. 6a is a vector diagram of winding voltage versus response current in a phase a power line leakage fault condition.
Fig. 6B is a vector diagram of winding voltage versus response current in a phase B power line leakage fault condition.
Fig. 6C is a vector diagram of winding voltage versus response current in the C-phase power line leakage fault condition.
Fig. 7a is a vector diagram of winding voltage and response current in a state where a phase a power line missed fault occurs simultaneously while B, C phase power lines are misconnected.
Fig. 7B is a vector diagram of winding voltage and response current in a state where a B-phase power line missed fault occurs simultaneously while A, C-phase power lines are misconnected.
Fig. 7C is a vector diagram of winding voltage and response current in a state where a C-phase power line missed fault occurs simultaneously while A, B-phase power lines are misconnected.
Detailed Description
The invention relates to a method for diagnosing connection faults of external cables of a permanent magnet synchronous motor, which is used for diagnosing connection faults of three-phase power cables and output cables of position sensors in a permanent magnet synchronous motor control system, wherein the control system consists of a rotating speed control module and a current control module, and the diagnosis method comprises the following steps of:
s1, inputting a zero-speed instruction to a rotating speed control module;
according to a permanent magnet synchronous motor voltage model and a back electromotive force model under a natural coordinate system:
in order to eliminate the influence of back electromotive force on the response of high-frequency injection, detecting faults before the motor starts to operate and timely removing the faults, and performing fault diagnosis at zero rotation speed and zero initial position;
s2, injecting a rotating high-frequency voltage signal into the current control module;
according to different types of injection signals, high-frequency signal injection is divided into voltage injection and current injection, the control stability of the voltage signal is higher than that of the current signal, the voltage signal is injected into a stator winding or a current control module, and the signal is directly injected into a direct axis (d axis) and a quadrature axis (q axis) of the current control module in a synchronous rotation coordinate system so as to avoid the influence of coordinate transformation; the signal form is mainly divided into rotation, pulse and square wave, wherein the steady state performance of rotation voltage injection is best, and dq axis coupling existing in the current control process can be completely eliminated through coordinate transformation under the injection of rotation voltage;
in the control system, two high-frequency voltage signals with a phase difference of 90 DEG are respectively injected into the d axis and the q axis of a current control module, wherein
Is the amplitude of the injection voltage, ">
Is the frequency of the injection voltage; />
Is the injection voltage at the synchronous rotation coordinateVector representations in the system;
s3, collecting and recording response current output by the controlled motor;
according to theoretical calculation, the response current output by the motor is related to the real-time position of the motor rotor, the amplitude of the high-frequency injection voltage and the phase sequence of the three-phase winding voltage of the stator, so that the cable fault of the motor control system can be reflected on the output response current;
s4, filtering high-frequency components in the response current, and extracting features;
filtering the output response current, and extracting a high-frequency component with the same amplitude as the injection voltage signal to be used as an original data set; extracting time domain features and frequency domain features of the original data set as feature value data of response current by using a feature extraction algorithm so as to enhance the accuracy of discrimination;
s5, carrying out model training by using a Support Vector Machine (SVM), judging whether an external cable connection fault occurs in the control system, and identifying the fault type;
in order to better describe the relationship between the fault data and the fault category of the controlled motor, accurate classification and identification are realized, and a motor operation data set is learned based on the basic principle of a support vector machine;
the motor responds to the characteristic value data of the current, a part of the characteristic value data is used as a training set to train an SVM model, and then relevant parameters are adjusted to achieve the highest classification precision aiming at each group of data sets; and the other part of data is used as a test set, the trained SVM model is used for offline classification, and the obtained fault diagnosis result is used as a reference, so that an operator can accurately remove the fault.
The diagnosis method carries out mathematical deduction aiming at thirteen representative fault phenomena, draws vector diagrams of input quantity and response quantity, intuitively reflects the phenomena of different types of faults in current response, and proves that the classification of the cable faults of the motor control system can be realized theoretically by analyzing the characteristics of amplitude, phase, included angle and the like of response current.
The permanent magnet synchronous motor control system is in a rotating speed closed-loop control mode with id=0.
The response current is input into the current control module in step S2 in the form of negative feedback.
The diagnostic method described is independent of the salient pole effect of the motor. The permanent magnet synchronous motors with different magnetic pole structures and different application functions can be used for diagnosing the motor cable connection faults by adopting the method.
The cable connection fault of the position sensor means that two output cables a and b of the position sensor such as the incremental encoder and the rotary transformer are reversely connected, so that the output real-time position and the actual position are exactly opposite.
The diagnosis scheme filters the collected response current, respectively filters a high-frequency component and a high-frequency negative sequence component, extracts the domain features and the frequency domain features, and inputs the extracted data into a support vector machine.
The diagnosis scheme uses a support vector machine to conduct optimized classification. The cable fault comprehensive diagnosis, classification and positioning with high accuracy are realized through machine learning without manual observation.
The diagnosis scheme passes the simulation test on the simulation platform and the physical platform. The classification accuracy of this strategy approaches or reaches 100% for different types of cable faults.
The diagnosis scheme can make 100% accurate fault discrimination and fault phase determination for the two-phase misconnection and single-phase misconnection of the three-phase power cable and the simultaneous occurrence of the two-phase misconnection and the single-phase misconnection; when the cable misconnection fault occurs, whether the misconnection fault is positioned in the three-phase power cable or the position sensor can be judged with the accuracy of more than 98%; the fault phase of the three-phase power cable can be positioned with 100% accuracy when the position sensor outputs the cable and the three-phase power cable simultaneously fail.
The invention will be further described with reference to the accompanying drawings.
In permanent magnet synchronous motors, typically, a three-phase power cable refers to a power line connecting an inverter and three-phase windings of the motor. The control voltage signal is transmitted from the driver to the controlled motor via the power line. The windings are subjected to electromagnetic induction to produce a response current.
Wherein the inverter output terminals are denoted A, B, C and the three-phase winding input terminals are denoted U, V, W. The correct attachment method is ABC-UVW. As long as the three-phase output terminals of the inverter are not arranged in order or have a certain phase output 0, it is called a three-phase cable connection error, and the erroneous cable connection may cause a failure. The three-phase connection error is divided into a phase sequence error and a phase failure. Phase sequence errors are divided into reverse ligation (ACB-UVW; CBA-UVW; BAC-UVW) and homonymous ligation (CAB-UVW; BCA-UVW). The diagnostic schemes described in the present invention do not discuss the case of a co-directional connection because their response currents differ from those of normal cases only by 120 ° of electrical rotation clockwise or counter-clockwise in phase angle, while the magnitudes remain consistent.
The phase failure refers to that for a three-phase winding, the input voltage of one phase is set to zero, and the phase sequence and the input value of the other phases are kept unchanged, and three conditions (0 BC-UVW; A0C-UVW; AB 0-UVW) exist; multiple faults refer to three cases (0 CB-UVW; C0A-UVW; BA 0-UVW) where phase sequence errors and phase defects occur. The remaining six types (B0C-UVW; CB0-UVW; AC0-UVW;0AC-UVW;0BA-UVW; A0B-UVW) are not discussed for reasons similar to the foregoing, the form and amplitude of the response current are the same, except that the phase angle is rotated by 120 degrees electrical degrees clockwise or counterclockwise.
The position sensor used in the driving system built by the invention is an incremental encoder which converts the relative displacement into a periodic electric signal capable of reflecting the real-time position and the real-time rotating speed of the motor rotor and returns to the motor speed control module to realize closed-loop negative feedback control. In the position sensor of the incremental encoder, three pulse signals are output from cables named a, b and Z, respectively. The Z line is used for positioning, and the form is different when the Z line is designed, so that the Z line is not confused with the a line and the b line. The output ports of the position sensor end and the input ports of the speed control end, which are connected with the two cables a and b, are respectively denoted as a ', b' and a '', b ''. If the two outgoing cables a, b are connected in opposite (a '-b ", b' -a"), the recorded rotation direction is opposite to the actual one and the resulting value of the real-time rotor position angle is also opposite to the actual one. The effect of the position sensor cable fault on the motor is similar to that caused by a reverse connection fault in a phase sequence error, so if a misconnection fault of three phase cables and a misconnection fault of the position sensor output cable occur simultaneously (a ' b ' -b ' a ' ', ACB-UVW; a ' b ' -b ' a ' ', CBA-UVW; a ' b ' -b ' a ' ', BAC-UVW), the fault type can only be determined by analyzing the current response.
And constructing a control model of the permanent magnet synchronous motor according to the theoretical deduction. In the control system structure shown in fig. 1, the sensor voltage output by the permanent magnet synchronous motor is converted into a response current through a voltage-current module; the permanent magnet synchronous motor outputs pulse count of relative displacement, and the pulse count is converted into signals reflecting the real-time position and the real-time speed of the rotor through the incremental encoder module. The three signals of the response current, the real-time position and the real-time rotating speed are connected into a speed control module shown in fig. 1 and a current control module shown in fig. 2 so as to realize closed-loop negative feedback control under high-frequency injection. In order to simulate the state of the permanent magnet synchronous motor after power-up and before starting, the speed command is specified as 0 as described in step S1. Whereas in the current control module shown in fig. 2, a given zero vector is used to define the initial position of the rotor as 0.
For injection of the rotating voltage signal, the injection voltage frequency should not exceed 50% of the PWM carrier frequency and the injection voltage amplitude should be less than 1/10 of the dc bus voltage amplitude in order to minimize the signal-to-noise ratio, as described in step S2.
As described in step S4, the adopted feature extraction algorithm extracts 13 time domain features and 13 frequency domain features in total.
In step S5, a support vector machine prediction model is built for classifying and diagnosing the cable faults of the permanent magnet synchronous motor. The support vector machine used is a C-type SVM
Incomplete classification is supported. Kernel function of support vector machine selectsRadial RBF kernel function->
. For the kernel coefficient g (gamma), first, the classification accuracy at the initial value, i.e., g=the reciprocal of the sample eigenvalue (g=1/num_features) is examined. If the accuracy is not sufficient, then starting from the initial value, each experiment is increased or decreased by a factor of 10 to find the most appropriate g value. For penalty coefficient c (cost_parameter), which is determined in the same way as g, starting from a default value of 1, a penalty coefficient value is selected for each group of data sets that maximizes classification accuracy by trial and error.
The fault diagnosis algorithm flow described in fig. 3 is not dependent on salient pole effect of the motor, is not limited by the topological structure and specific parameters of the motor, and is a general motor external control system cable fault comprehensive diagnosis algorithm.
And extracting a time-frequency domain characteristic value from the acquired response current signal to serve as a training set, training an SVM model, and performing off-line comprehensive fault diagnosis. According to the diagnosis method, 95.7143% -100% fault identification precision is achieved for thirteen cable faults on the simulation platform and the physical platform, cable connection faults outside a motor control system can be accurately detected and diagnosed, fault sources are positioned, and therefore reliability of the system is improved. In particular, the mathematical models and fault phenomena of the position sensor cable faults and the three-phase power cable faults are highly similar, and the distinguishing precision of the two faults in the invention reaches 99.4286 percent and 98.6667 percent respectively on a simulation platform and a physical platform.
It is to be understood that the foregoing is illustrative of the present invention and is not to be construed as limiting the scope of the invention, and that various equivalent modifications to the disclosed embodiments are intended to be within the scope of the appended claims.
Claims (10)
1. The method is characterized by diagnosing connection faults of three-phase power cables and position sensor output cables in a permanent magnet synchronous motor control system, wherein the control system consists of a rotating speed control module and a current control module, and the diagnosis method comprises the following steps of:
s1, inputting a zero-speed instruction to a rotating speed control module;
in order to eliminate the influence of back electromotive force on the response of high-frequency injection, fault diagnosis is carried out at the zero rotating speed and the zero initial position; inputting 0 as a given reference rotation speed to a motor rotation speed control module; the voltage model and the back electromotive force model of the permanent magnet synchronous motor under the natural coordinate system are as follows:
u a 、u b 、u c three-phase voltage i of stator winding of permanent magnet synchronous motor a 、i b 、i c R is three-phase current of stator winding s Is the stator resistance of the three-phase permanent magnet synchronous motor, L 3s For the stator inductance matrix, i.e. the sum of the three-phase winding self inductance and mutual inductance,
representing a differential operator over time; EMF (electromagnetic wave) device a 、EMF b 、EMF c For three-phase back EMF, the scaling factor k is a normal number, ψ f Is the rotor flux linkage omega e Is the real-time rotating speed of the motor, theta e Is the real-time position of the motor rotor; when the motor rotor is in zero position, the counter electromotive force of the A phase is zero, and the counter electromotive force of the BC phase still exists; when the rotating speed of the motor is zero, the three-phase back electromotive force is fully restored to zero;
in order to eliminate the influence of back electromotive force on the response of high-frequency injection, detecting faults before the motor starts to operate and timely removing the faults, and performing fault diagnosis at zero rotation speed and zero initial position;
s2, injecting a rotating high-frequency voltage signal into the current control module;
in the control system, two high-frequency voltage signals with a phase difference of 90 DEG are respectively injected into the d axis and the q axis of a current control module, wherein v c Is the amplitude, omega of the injection voltage c ＝2πf c Is the frequency of the injection voltage;
is a vector representation of the injection voltage in a synchronous rotating coordinate system;
s3, collecting and recording response current output by the controlled motor;
according to theoretical calculation, the response current output by the motor is related to the real-time position of the rotor, the amplitude of the high-frequency injection voltage and the sequence of the three-phase winding voltages of the stator, so that the cable faults of the motor control system can be reflected on the output response current;
s4, filtering high-frequency components in the response current, and extracting features;
filtering the output response current, and extracting a high-frequency component with the same amplitude as the injection voltage signal to be used as an original data set; extracting time domain features and frequency domain features of the original data set as feature value data of response current by using a feature extraction algorithm so as to enhance the accuracy of discrimination;
s5, performing model training by using a support vector machine (support vector machine, SVM), judging whether an external cable connection fault occurs in the control system, and identifying the fault type;
in order to better describe the relationship between the fault data and the fault category of the controlled motor, accurate classification and identification are realized, and a motor operation data set is learned based on the basic principle of a support vector machine;
the motor responds to the characteristic value data of the current, a part of the characteristic value data is used as a training set to train an SVM model, and then relevant parameters are adjusted to achieve the highest classification precision aiming at each group of data sets; and the other part of data is used as a test set, the trained SVM model is used for offline classification, and the obtained fault diagnosis result is used as a reference, so that an operator can accurately remove the fault.
2. The method for diagnosing an external cable connection fault of a permanent magnet synchronous motor according to claim 1, wherein the permanent magnet synchronous motor control system is i d Magnetic field directional control mode with zero direct current of =0, by setting direct current i in current control module d The zero setting mode is used for avoiding the demagnetization of the direct shaft, eliminating the direct shaft armature reaction of the permanent magnet synchronous motor, keeping the good magnetism of the permanent magnet used for excitation and improving the utilization rate of the conversion of the electric energy of the motor into mechanical energy.
3. The method for diagnosing a fault in an external cable connection of a permanent magnet synchronous motor according to claim 1, wherein the response current in step S3 is continuously returned to the current control module in step S2 in a form of negative feedback.
4. The method for diagnosing a fault in connection with an external cable of a permanent magnet synchronous motor according to claim 1, wherein the fault in connection with the output cable of the position sensor refers to a sequential exchange of two output cables A, B of the incremental encoder and the rotary transformer, so that the real-time position and the actual position of the rotor of the output motor are in opposite numbers.
5. The method for diagnosing a fault in an external cable of a permanent magnet synchronous motor according to claim 1, wherein the three-phase power cable means a power line connecting an inverter and a three-phase stator winding of the motor, a control voltage signal is transmitted from a driver to a controlled motor through the power line, and a response current is generated on the winding through electromagnetic induction.
6. The method for diagnosing a fault in connection with an external cable of a permanent magnet synchronous motor according to claim 1, wherein the support vector machine used in step S5 is a C-type SVM, and the corresponding parameter S is set to-s=0, supporting incomplete classification; the kernel function of the support vector machine selects a radial kernel function (radial basis function, RBF), also known as a gaussian kernel function, whose corresponding parameter t is set to-t=2.
7. The method for diagnosing a fault of an external cable of a permanent magnet synchronous motor according to claim 1, wherein the original data set in step S4 further includes a high-frequency negative sequence response current, and the high-frequency negative sequence response current has position information, is not affected by the rotation speed of the rotor and the fault of the sensor, and can be used as one of the basis of fault diagnosis; negative sequence components of the high frequency response current are filtered by a synchronous shafting filter (synchronous reference frame filter, SRFF) and are jointly output from the control system as an original data set.
8. The method for diagnosing a permanent magnet synchronous motor external cable connection fault according to claim 1, wherein the response current in step S3 is converted from the sensor voltage outputted from the motor via a voltage-current module.
9. The method for diagnosing the connection fault of the external cable of the permanent magnet synchronous motor according to claim 1, wherein the method for diagnosing the connection fault of the external cable is independent of the salient pole effect of the motor, and the permanent magnet synchronous motor with different magnetic pole structures and different application functions can diagnose the connection fault of the cable of the motor by adopting the method.
10. The method for diagnosing an external cable connection fault of a permanent magnet synchronous motor according to claim 1, wherein the method for diagnosing an external cable connection fault makes fault discrimination and fault phase determination with 100% accuracy for two-phase misconnection, single-phase misconnection and simultaneous occurrence of two-phase misconnection and single-phase misconnection of a three-phase power cable; when the cable misconnection fault occurs, judging whether the misconnection fault is positioned in the three-phase power cable or the position sensor with the accuracy of more than 98%; when the position sensor outputs the cable and the three-phase power cable simultaneously fail, the failure phase of the three-phase power cable is positioned with 100% accuracy.
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